Enhancing Malva sylvestris extract properties through lactic acid bacteria fermentation: impact on phytochemical profile and bioactivity
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract This study investigates the fermentation of Malva sylvestris aerial parts using three lactic acid bacteria: Lactiplantibacillus plantarum 299V, Pediococcus acidilactici IRZ12B, and Lacticaseibacillus rhamnosus GG. The fermentation process resulted in a notable increase in microbial counts of LAB populations, production of organic acids, reduction of antinutritional factors such as tannins, and enhancement the bioavailability of some essential minerals. Post-fermentation analyses revealed a threefold increase in total phenolic content compared to the non-fermented extract. Antioxidant activity also showed a substantial enhancement, with L. plantarum 299V and P. acidilactici IRZ12B nearly doubling the DPPH inhibition percentage, while L. rhamnosus GG exhibited no improvement. Furthermore, antimicrobial activity varied among strains, with P. acidilactici IRZ12B and L. rhamnosus GG effectively inhibiting Y. enterocolitica growth, while all fermented samples significantly reduced S. enterica proliferation. These findings support the use of lactic acid bacteria fermentation as a bioprocess to improve the phytochemical profile of malva, with potential therapeutic applications. Furthermore, the optimized fermentation conditions could facilitate the incorporation of fermented malva as a functional ingredient in plant-based foods, aligning with the growing consumer demand for health-oriented products. Graphical Abstract
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it